MOTION MODELING IN VISUAL TRACKING

• US 20150228118A1
• Filed: 02/12/2014
• Published: 08/13/2015
• Est. Priority Date: 02/12/2014
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Inventors: Eade, Ethan, Ebstyne, Michael John, Steedly, Drew, Schaffalitzky, Frederick
• Granted Patent: US 9,767,609 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G02B 2027/0178 Eyeglass type eyeglass details G02C
• CPC Class Codes: G02B 27/017 Head mounted
• CPC Class Codes: G06F 3/012 Head tracking input arrangements
• CPC Class Codes: G06F 3/013 Eye tracking input arrangements G06F3/015 takes precedence
• CPC Class Codes: G06F 3/017 Gesture based interaction, e.g. based on a set of recognized hand gestures interaction based on gestures traced on a digitiser G06F3/04883
• CPC Class Codes: G06T 19/006 Mixed reality object pose determination, tracking or camera calibration for mixed reality G06T7/00

Abstract

Embodiments are disclosed that relate to determining a pose of a device. One disclosed embodiment provides a method comprising receiving sensor information from one or more sensors of the device, and selecting a motion-family model from a plurality of different motion-family models based on the sensor information. The method further comprises providing the sensor information to the selected motion-family model and outputting an estimated pose of the device according to the selected motion-family model.

Claims

1. A method of assessing a pose of a device, the method comprising:

receiving sensor information from one or more sensors of the device;

selecting a motion-family model from a plurality of different motion-family models based on the sensor information;

providing the sensor information to the selected motion-family model; and

outputting an estimated pose of the device according to the selected motion-family model.

2. The method of claim 1, wherein the device is a head-mounted display device configured to output displayed content to a wearer of the device.

3. The method of claim 2, further comprising adjusting one or more display properties for the displayed content based on the estimated pose of the device.

4. The method of claim 1, wherein outputting the estimated pose of the device further comprises providing the sensor information and an output of the selected motion-family model to a pose filter and outputting the estimated pose of the device from the pose filter.

5. The method of claim 1, wherein the sensor information indicates a physical state of a wearer of the device, the physical state indicating one or more of a position, orientation, and movement characteristic of the wearer.

6. The method of claim 1, wherein selecting the motion-family model comprises classifying a family of motion exhibited by the device and comparing the classified family of motion to one or more families of motion associated with the plurality of different motion-family models.

7. The method of claim 6, wherein classifying the family of motion exhibited by the device comprises determining the family of motion based on a previously-output estimated pose of the device.

8. A head-mounted display device comprising:

a sensor;

a logic machine; and

a storage machine, the storage machine configured to hold instructions executable by the logic machine to;

receive sensor information from the sensor;

select a motion-family model from a plurality of motion-family models based on a physical state of a wearer of the head-mounted display device;

provide the sensor information and an output of the selected motion-family model to a pose filter; and

output, from the pose filter, an estimated position and orientation of the head-mounted display device based on the sensor information and the selected motion-family model.

9. The head-mounted display device of claim 8, wherein the physical state of the wearer is determined based on the sensor information from the sensor.

10. The head-mounted display device of claim 8, wherein the sensor information includes one or more measurements of a position and/or orientation of a head of the wearer.

11. The head-mounted display device of claim 10, wherein the motion-family model matches the one or more measurements to a selected trajectory of head movement based on the physical state of the wearer.

12. The head-mounted display device of claim 8, wherein the pose filter includes a Kalman filter.

13. The head-mounted display device of claim 8, wherein selecting the motion-family model from the plurality of motion-family models further comprises sending the sensor information and a previously-output estimated position and orientation to a motion behavior classifier of the head-mounted display device.

14. The head-mounted display device of claim 13, wherein the sensor information is provided to the pose filter and the motion behavior classifier.

15. The head-mounted display device of claim 13, wherein the motion behavior classifier is configured to analyze the sensor information and the previously-output estimated position and orientation to select the motion-family model.

16. The head-mounted display device of claim 15, further comprising changing the motion-family model if the selected motion-family model is different than a current motion-family model.

17. A storage machine holding instructions executable by a logic machine to:

collect sensor information from one or more sensors of a head-mounted display;

send the sensor information to a motion behavior classifier for determining a selected motion-family model from a plurality of different motion-family models based on the sensor information;

in response to determining that the selected motion-family model is different than a previously-used motion-family model, replacing the previously-used motion-family model with the selected motion-family model; and

outputting a time-varying pose estimate that is based on both the previously-used motion-family model and the selected motion-family model.

18. The storage machine of claim 17, wherein a first, earlier time-varying pose estimate is based on the previously-used motion-family model and a second, later time-varying pose estimate is based on the selected motion-family model.

19. The storage machine of claim 17, wherein a first, earlier time-varying pose estimate is based on the previously-used motion-family model and a second, later time-varying pose estimate is based on an average of an output of the previously-used motion-family model and the selected motion-family model.

20. The storage machine of claim 17, wherein one or more of the sensor information and the time-varying pose estimate is provided to a Kalman filter.